Academic journal article Memory & Cognition

Using Response Time Modeling to Distinguish Memory and Decision Processes in Recognition and Source Tasks

Academic journal article Memory & Cognition

Using Response Time Modeling to Distinguish Memory and Decision Processes in Recognition and Source Tasks

Article excerpt

Published online: 8 August 2014

© Psychonomic Society, Inc. 2014

Abstract Receiver operating characteristic (ROC) functions are often used to make inferences about memory processes, such as claiming that memory strength is more variable for studied versus nonstudied items. However, decision processes can produce the ROC patterns that are usually attributed to memory, so independent forms of data are needed to support strong conclusions. The present experiments tested ROC-based claims about the variability of memory evidence by modeling response time (RT) data with the diffusion model. To ensure that the model can correctly discriminate equal- and unequal-variance distributions, Experiment 1 used a numerousity discrimination task that had a direct manipulation of evidence variability. Fits of the model produced correct conclusions about evidence variability in all cases. Experiments 2 and 3 explored the effect of repeated learning trials on evidence variability in recognition and source memory tasks, respectively. Fits of the diffusion model supported the same conclusions about variability as the ROC literature. For recognition, evidence variability was higher for targets than for lures, but it did not differ on the basis of the number of learning trials for target items. For source memory, evidence variability was roughly equal for source 1 and source 2 items, and variability increased for items with additional learning attempts. These results demonstrate that RT modeling can help resolve ambiguities regarding the processes that produce different patterns in ROC data. The results strengthen the evidence that memory strength distributions have unequal variability across item types in recognition and source memory tasks.

Keywords Diffusion model · Recognition memory · Source memory · Unequal variance assumption

When we look back on an event, what kind of information do we get from memory? Subjectively, we reexperience a some- what degraded version of the perceptions, actions, thoughts, and emotions that characterized the event, but how is this information translated into explicit decisions about what we have and have not experienced in the past? Theorists from a variety of perspectives propose that all of the different types of remembered information vary on a continuum of strength, and the total evidence that an event was experienced is defined by combining these strength values (Johnson, Hashtroudi, & Lindsay, 1993; Ratcliff, 1978; Wixted, 2007).

Researchers have often attempted to test hypotheses about memory evidence using receiver operating characteristic (ROC) functions, which plot the proportion of times a re- sponse is made correctly on the proportion of times it is made incorrectly across different levels ofbias (Egan, 1958; Wixted, 2007). The different bias levels are almost always created by having participants respond on a confidence scale. Conclu- sions about memory rely on the assumption that properties of the ROC function-such as asymmetry in the function or the degree of curvature-are a consequence of underlying mem- ory processes. However, ROC properties can also be influ- enced by decision processes. For example, ROC asymmetry and curvature can be affected by differences in decision criteria for the different response alternatives in sequential sampling models (Ratcliff & Stams, 2009, 2013; Van Zandt, 2000), changes in the decision criteria on one evidence di- mension across different levels of another dimension (Stams, Pazzaglia, Rotello, Hauttrs, & Macmillan, 2013; Stams, Rotello, & Hauttrs, 2014), and variability in the position of decision criteria across trials (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008).

A critical goal for advancing memory research is distinguishing which ROC results are properly interpreted in terms of memory evidence and which are produced by deci- sion mechanisms. My primary goal was to model response time (RT) distributions from memory tasks to determine whether RT data support the same conclusions about memory as ROC analyses. …

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